Single-machine deployment

A single-machine deployment provides the same components as a multi-node setup, with all services running on a single machine. Based on the architecture outlined in the dedicated section, a single-machine deployment can be represented as follows:

This page provides instructions for installing, updating, and uninstalling the Aindo Synthetic Data Platform in a single-machine setup.

Installation

Step 1 - Install k3s

The first step is to install k3s, a lightweight Kubernetes distribution capable of running on a single node. For comprehensive installation instructions, refer to the official documentation. To install k3s on an Ubuntu server, the key steps are the following:

sudo apt-get update
sudo apt-get upgrade
curl -sfL https://get.k3s.io | INSTALL_K3S_EXEC="server"  sh -s - --disable traefik

To confirm that k3s is running, use this command:

sudo kubectl get nodes

The expected output should be similar to:

NAME               STATUS   ROLES                  AGE   VERSION
ip-172-31-22-230   Ready    control-plane,master   1m    v1.31.4+k3s1

Step 2 - Install the NGINX controller

Next, we install the NGINX ingress controller using a Helm chart. Create a YAML file named nginx.yaml with the following content:

apiVersion: helm.cattle.io/v1
kind: HelmChart
metadata:
  name: ingress-nginx
  namespace: kube-system
spec:
  repo: https://kubernetes.github.io/ingress-nginx
  chart: ingress-nginx
  createNamespace: true
  version: 4.12.0
  targetNamespace: ingress-nginx
  valuesContent: |-
    controller:
      ingressClassResource:
        default: true

Apply the configuration using:

sudo kubectl apply -f nginx.yaml

To check that the NGINX controller is running, execute:

sudo kubectl get pods -n ingress-nginx

and the output from the command line should look like this:

NAME                                        READY   STATUS    RESTARTS   AGE
ingress-nginx-controller-7657f6db5f-gblxh   1/1     Running   0          23s

Step 3 - Configure the Storage class

The third step involves creating a storage class with a Retain reclaim policy. Create a YAML file named storage.yaml with the following content:

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: local-path-retain
provisioner: rancher.io/local-path
reclaimPolicy: Retain
volumeBindingMode: WaitForFirstConsumer

Apply the configuration using:

sudo kubectl apply -f storage.yaml

To verify that the storage class is available, run:

sudo kubectl get storageclass

The output should look similar to this:

NAME                   PROVISIONER             RECLAIMPOLICY   VOLUMEBINDINGMODE      ALLOWVOLUMEEXPANSION   AGE
local-path (default)   rancher.io/local-path   Delete          WaitForFirstConsumer   false                  2m
local-path-retain      rancher.io/local-path   Retain          WaitForFirstConsumer   false                  6s

Step 4 - Create the namespace and the pull secret

Create the aindo namespace with:

sudo kubectl create namespace aindo

To verify that the namespace was created:

sudo kubectl get namespace aindo

The output should be similar to this:

NAME    STATUS   AGE
aindo   Active   2s

Next, create the docker-registry-secret secret using the credentials provided by Aindo:

sudo kubectl create secret docker-registry docker-registry-secret -n aindo --docker-server=https://index.docker.io/v1/ --docker-username=DOCKER_USER --docker-password=DOCKER_PASSWORD

To verify that the secret has been created, run:

sudo kubectl get secret docker-registry-secret -n aindo

Expected output:

NAME                     TYPE                             DATA   AGE
docker-registry-secret   kubernetes.io/dockerconfigjson   1      2s

Step 5 - Deploy the Aindo Synthetic Data Platform

Create a YAML file named aindo-deploy.yaml with the following content:

apiVersion: helm.cattle.io/v1
kind: HelmChart
metadata:
  name: aindo-release
  namespace: aindo
spec:
  chart: oci://registry-1.docker.io/aindo/aindo-data-platform
  version: 1.2.1
  dockerRegistrySecret:
    name: docker-registry-secret
  targetNamespace: aindo
  valuesContent: {}

Update the valuesContent field with the specific configuration for your deployment. Deploy the Aindo platform by running:

sudo kubectl apply -f aindo-deploy.yaml

To verify that the application has been deployed:

sudo kubectl get pods -n aindo

The expected output should look like this:

NAME                                                       READY   STATUS    RESTARTS   AGE
aindo-aindo-data-platform-api-84d9fb9f86-l5j7l             1/1     Running   0          2m
aindo-aindo-data-platform-fe-deploy-5c99d989bf-44j8g       1/1     Running   0          1m
aindo-aindo-data-platform-worker-ai-b9897ccbb-spjsk        1/1     Running   0          1m
aindo-aindo-data-platform-worker-default-9898f5b8b-5lvb8   1/1     Running   0          1m
aindo-aindo-data-platform-worker-dlq-5544d77-m92ht         1/1     Running   0          1m
aindo-minio-fc6875df-zlqld                                 1/1     Running   0          2m
aindo-postgresql-0                                         1/1     Running   0          2m
aindo-redis-master-0                                       1/1     Running   0          2m

Updating

To update the deployment, apply required changes to the aindo-deploy.yaml file and run:

sudo kubectl apply -f aindo-deploy.yaml

Uninstallation

To uninstall the deployment, run:

sudo kubectl delete -f aindo-deploy.yaml